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import os
from kg_rag.utility import config_data
def download_llama(method):
from kg_rag.utility import llama_model
try:
llama_model(config_data["LLAMA_MODEL_NAME"], config_data["LLAMA_MODEL_BRANCH"], config_data["LLM_CACHE_DIR"], method=method)
print("Model is successfully downloaded to the provided cache directory!")
except:
print("Model is not downloaded! Make sure the above mentioned conditions are satisfied")
print("")
print("Starting to set up KG-RAG ...")
print("")
# user_input = input("Did you update the config.yaml file with all necessary configurations (such as GPT .env path, vectorDB file paths, other file paths)? Enter Y or N: ")
# print("")
# if user_input == "Y":
if True:
print("Checking disease vectorDB ...")
print("The current VECTOR_DB_PATH is ", config_data["VECTOR_DB_PATH"])
try:
if os.path.exists(config_data["VECTOR_DB_PATH"]):
print("vectorDB already exists!")
else:
print("Creating vectorDB ...")
from kg_rag.vectorDB.create_vectordb import create_vectordb
create_vectordb()
print("Congratulations! The disease database is completed.")
except:
print("Double check the path that was given in VECTOR_DB_PATH of config.yaml file.")
'''
print("")
user_input_1 = input("Do you want to install Llama model? Enter Y or N: ")
if user_input_1 == "Y":
user_input_2 = input("Did you update the config.yaml file with proper configuration for downloading Llama model? Enter Y or N: ")
if user_input_2 == "Y":
user_input_3 = input("Are you using official Llama model from Meta? Enter Y or N: ")
if user_input_3 == "Y":
user_input_4 = input("Did you get access to use the model? Enter Y or N: ")
if user_input_4 == "Y":
download_llama()
print("Congratulations! Setup is completed.")
else:
print("Aborting!")
else:
download_llama(method='method-1')
user_input_5 = input("Did you get a message like 'Model is not downloaded!'? Enter Y or N: ")
if user_input_5 == "N":
print("Congratulations! Setup is completed.")
else:
download_llama(method='method-2')
user_input_6 = input("Did you get a message like 'Model is not downloaded!'? Enter Y or N: ")
if user_input_6 == "N":
print("""
IMPORTANT :
Llama model was downloaded using 'LlamaTokenizer' instead of 'AutoTokenizer' method.
So, when you run text generation script, please provide an extra command line argument '-m method-2'.
For example:
python -m kg_rag.rag_based_generation.Llama.text_generation -m method-2
""")
print("Congratulations! Setup is completed.")
else:
print("We have now tried two methods to download Llama. If they both do not work, then please check the Llama configuration requirement in the huggingface model card page. Aborting!")
else:
print("Aborting!")
else:
print("No problem. Llama will get installed on-the-fly when you run the model for the first time.")
print("Congratulations! Setup is completed.")
'''
else:
print("As the first step, update config.yaml file and then run this python script again.")
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